Visual Design & Analysis

Visualizations of Habit and Routine

2009-04-08T15:53:00.018Z

Lately I've become interested in the design of visualizations that draw out patterns in habit & routine. To explain what I mean, here are a bunch of nice examples...

Let's start with a visualization of a twitter user's posting habits from xefer.com:

This simple diagram of a baby's sleep times comes from Trixie Tracker:
Simple but effective! Thanks to Nathan's flowingdata for these two examples. (See also a wonderful visualization of the stabilization of a baby's sleep patterns in Winfree "The Timing of Biological Clocks" Page 31, also shown in Card et al "Information Visualization..." Page 5/6).

It seems that some form of heatmap is the most common means of representing habitual behaviours - see e.g., Andrienko et al for a visualization of traffic densities around Milan (red is lots of traffic):
This picture of hotel visitation patterns (Weaver et al) shows the number of visitors over a weekly timescale:
I like the summary at the bottom and right of the main area showing aggregated trends.

Nathan Eagle & Alex Pentland's paper on "Eigenbehaviours" differentiates various routine patterns from a dataset & presents them clearly:
This reminds me of Wijk & Selow's classic paper too.

Does anyone have any suggestions on other visualizations of habits and routines?

Summer internship at i2, Cambridge UK

2009-02-27T15:30:00.006Z

Time for a shameless plug! If there are any students of information visualization out there looking for an interesting internship this summer - my company is offering one. Looking forward to hearing from you...

The Search Box

2008-09-02T07:02:00.010Z

I've been a fan of Google Suggest since I first saw it - and I think that the news that it will now become the default experience for all Google searches is very significant because it will change everyone's expectations of what should happen when they start typing into a search box everywhere:

Of course several search boxes already do this kind of thing (the search box & 'awesome bar' in Firefox 3, the 'omnibox' in Google Chrome) but I believe that its use will become widespread not just for web based searching but also within desktop applications.

In 2005 just after Google Suggest came out I implemented my own version of it - it doesn't take much to get the basics right - you just need a reverse index. A bit more work and some stats can help eliminate common 'stop words' & give spelling suggestions; some further work and you can index two or three word phrases. Some of this stuff ended up in a desktop product in my day job.

Of course in a disconnected desktop product one doesn't have the huge amount of statistical information on what is searched for & clicked on, but to get a simple version of 'suggest' up and running can be quite quick and gives the user real tangible benefits.

The search box _should_ never be the same again...

Visualizaton Goals & Features

2008-08-06T12:36:00.011+01:00

What are the goals of visualization? And what are the features that support those goals?

My 10 cents worth:

The basic goal is to facilitate reasoning and thought about what is being visualized. That reasoning could revolve around causality, hypothesis, predictions, inferences, habits, modus operandi, contradictions, uncertainty, and a whole host of problems the user is trying to solve. Often the reasoning revolves around external data and/or knowledge too. Visualization should expose structure in the data such as patterns, clusters, gaps, bursts of activity, outliers & trends, etc. And at the end of the reasoning process the great thing about visualization is that one should end up with a picture that can be used to disseminate one's insights to other people.

So what key features enable these goals to be achieved?
* A Summarization/Overview to give the big picture
* Zoomability
* Drill-down on data for the detail
* Easy navigation around the visual
* Filtering information by category or query
* Different types of visualization expose different patterns (geographic, timeline, textual, lists, link diagrams, etc.)
* Brushing & linking visualizations together can help the filtering & exploration

Other basic things which must be in place in order to succeed:
* Ease of import and export - and adhering to any standards
* Some basic searching of the data
* One must be able to read the data - in particular any text
* Scaling well as the data size gets very large
* Links out to other systems for further information is key
* Links back in to the visualization from other systems can also be powerful
* Interoperability with other visualization tools and other applications in general
* Commentary, scribbling and drawing on the visualizations is a great way to add understanding - a picture alone is rarely enough

And don't forget the more esoteric things too:
* It needs a positive emotional response so it must look good and not conflict with user's expectations
* It can use standard visual symbolism, conventions & metaphors
* It must use the basic visual variables well (shape, colour, position, etc.)
* Transitions between visualizations must be smooth to allow the user to keep their context
* It should use design techniques like 'information scent' & obvious affordances
* It should facilitate playfulness where ever possible - don't punish 'mistakes'!

Phew - glad I got that off my chest - back to the day job :-)

Intellipedia

2008-07-15T21:06:00.010+01:00

I can't remember when I first read about Intellipedia, but I know it was a long time ago. The other day I watched a really inspirational video from the people inside the CIA who successfully overcame typical middle-management obstacles in order to produce it. I particularly like their comments on the evils of email and shared drives for collaboration. The original proposal document is also well worth a read.

Interesting too that Intellipedia's iVideo sharing component reportedly uses Adobe Flash, but there is no public mention of using visualization tools yet, despite visualization techniques being widely used in the intelligence analysis community.

Details Matter

2008-07-10T20:11:00.007+01:00

Recently I've noticed a few examples where smallish visual design details really matter.

What Colin Ware in "Visual Thinking for Design" refers to as "multiscale structure" in shown-off very effectively in Vizster and SocialAction.

Another example is the way that Thinkbase constructs links of similar types:

Notice how the actors & roles aren't linked directly to the film but go via intermediate nodes. And also see how well the space is used and how the links are similar lengths & short - both of these are great for aesthetics and link-following tasks.

Both these approaches build on the position visual variable to effectively to 'clump' the like-nodes together. But these designs also add other visual variables (connecting line, enclosing shape) which assist visual pattern finding, and importantly can offer affordances for interactivity too.

My Day Job

2008-06-06T20:37:00.016+01:00

Here's what I've been doing these last few months -

As you can see, I've been working on a collaboration system for intelligence analysts. (Hence the guns & crimes!)

It is all written using Adobe tools - Flex and Flash - so people just need to click a link to launch the application in their browser, which is seriously cool. We've designed it to work with touch screens so you just need one press to drill down on the data.

So far it has gone really well & now that we've done the basics I'm hoping to get some innovative visualizations in there too. Watch this space...!

Update 1: "The better part of valour is discretion..." - I've decided to remove the video for now while I sort out whether my employers are happy for me to show it. With a bit of luck it will be back soon! Joe

Update 2: It seems that it is fine to air this after all.

Design & Reach

2007-11-30T13:49:00.000Z

Following on from my last post, Mike Danziger and I chatted on email & he wrote up some impressions of the InfoVis conference. Stephen Few responded to some of the points, and a couple (1, 2) of subsequent postings, and some other comments (3, 4) have shown that people are interested. Sorry for being so late in responding myself - the day job sometimes gets in the way!

For me, the key contribution has been Pat Hanrahan's. I feel the same way & I'm grateful to him for providing some academic respectability to what would otherwise just be my own opinions. From my own pragmatic software industry perspective, I'd like to say something about how his suggestions could be taken forward.

Delivery mechanisms are key: to appeal to the masses one needs reach. Interactive visualizations must be delivered to people's eyes & to their fingertips. Static images in papers aren't enough: people don't have much time or patience & won't enjoy having to read lots of text in order to learn how the interaction works.

One approach is to put good visualization capability into commonly used tools such as Excel (1). That way people can manage their data themselves. Because the user has the ability to load and edit the data behind the visualizations this means a high degree of skill is needed when crafting the software so it has the necessary flexibility. Each tool has different extension points & platforms. In practical terms this means a software company is forced to choose a very small list of supported environments & work flows.

The more obvious route is to exploit the immediacy and universality of web delivery mechanisms. Thanks to Flash, Silverlight & Java there is a huge audience out there with suitable runtimes. It is good to see more and more experimental visualizations using these. (Though problems with data management are still there of course...)

Reach isn't enough: in order to bring something compelling to people one must embrace designers. Graphic designers, user experience designers, interaction designers, the works! The right kind of designers can keep a visualization clean, useful & informative but also imbue it with style, panache & memorability. There is a design revolution happening now in the software industry & it will sweep up information visualization tools along the way.

The combination of the need for reach and good design is the main reason why I'm so interested in the Adobe platform. Because they already have designers using their tools, they don't need to woo them to new platform. Add a massive install base (flash) and increasingly workable languages (mxml, as3) and it is hard to dismiss. Nice to see I'm not alone in thinking this.

Sacramento Thoughts

2007-11-08T18:19:00.000Z

I got back from the IEEE Visualization conference in Sacramento a few days ago - it was highly enjoyable and I met some great people there.

I've been struggling to come to terms with the quantity of reading I now have to do. I've also found it hard to summarize my thoughts on all that I heard.

I think my personal best paper award would go to Jeff Heer's "Design Considerations for Collaborative Visual Analytics".

On a similar topic, Fernanda Viégas said something that caught my attention: instead of focusing on the classic visualization question of scaling the amount of data being visualized, the Many-Eyes project scales the size of the audience.

However, each data set in the Many-Eyes site is isolated. Processing of the data has to be done in advance in order to bring it down to a manageable size, and data sets do not have any intersection points with each other. (Although they do allow comments to refer to other data sets, along with other navigation aids.)

Classic information visualization research seems to follow a pattern something like this:
* Researcher gets hold of a dataset from somewhere.
* They consider various encodings of it.
* While doing that they achieve some level of domain knowledge.
* They develop an isolated visualization system - this is what they spend most of their time on (I can't blame them - it is the fun bit).
* They achieve some insights of their own which gives them a warm glow.
* Some short evaluation is tacked on to keep the reviewers happy when they get the paper.

From an outsider's perspective:
* In many cases the dataset is considered in isolation from other potentially interesting & relevant data sets.
* The quality of the encodings chosen depends on the knowledge of the researcher, and this can vary quite a bit.
* The system developed tends to be isolated from other applications & systems - that makes it easier to develop. Often there are no multi-user aspects, but this at least seems to be changing.
* Insights almost always are with regard to knowledge gleaned from outside the data set. E.g., a downturn in the number of farmers (in census data) could be explained by increasing agricultural mechanisation (innate knowledge), or the popularity of a certain baby name might coincide with a celebrity (search for 'Celine' here). There is often an implied "cause and effect" hypothesis in these kind of insights.

Going back to Viégas' comments I suspect that the true problem lies in scaling not just the audience - though that of course is important - but scaling on both the number and type of datasets being visualized.

The 'perfect visualization tool' would be able to cope with new data sets being thrown at it. Linkage would be automatically established between elements of the data set (e.g., Joe Bloggs from one data set would be recognised as the same Joe Blogs from another data set). The data sets could have a wide variety of schemas and come from wildly different sources. The various visualizations in the tool would be automagically updated with the relevant encoding of the new data, and new visualizations which have suddenly become appropriate would be displayed. The user would be able to reach many new insights because all the data is cross-referenced and generally speaking most insights come when combining data. Plus the visualization, being perfect, would show those insights clearly.

Mike Cammarano's talk on his work with the dbpedia data was interesting from this angle, in that the data was inherently heterogeneous & extensible. Of course, the Semantic Web research agenda is of interest here too, despite lying outside of information visualization research.

As Matthew Ericson showed, the sheer craft and skill needed to combine data well and communicate it effectively means that it is difficult to see a perfect visualization tool being realised in an automated way. I guess this makes it an interesting research area!

Another aspect of developing web-based social visualizations is that there is much more potential for gathering information about how users actually use the visualizations: server-side logs can be designed to keep track of almost every action. This would lack the rigour of a properly controlled lab experiment, but that would be counterbalanced by the sheer number of possible users, so I'd say there must be huge benefits in this approach. (And of course making sense of the logs could be another data visualization challenge!)

On a separate topic I found Stephen Few's capstone talk rather unsettling - I understand why he is so passionate about designing clear visuals, but sometimes that passion can err on the abrasive side. And that style won't endear the visualization community to the world out there. I also think he underestimates the power of playfulness and fun in reaching out to an audience - come on - Swivel's option to 'bling your graph' is just funny! Another worry is that the very Spartan style of visuals he favours actually imposes an aesthetic in its own right, for all of its good intentions and intelligent rationale. We should accept some people just won't like that aesthetic.

However, his tutorial was a really excellent Tuftean summary of all that is great and good about the subject, so I guess he can be forgiven! And when you see graphics like graphwise (thanks Nathan) you can see how much work there is to be done :-)

Visual Variables

2007-08-29T09:17:00.000Z

I've been designing some new visualizations recently, and reading around the InfoVis literature for examples to analyse and best practices to follow. I've found myself returning again and again to a diagram in MacKinlay's 1986 paper and various papers which follow it. So much so that I've reworked a version of the diagram and pinned it to the wall behind my desk for quick reference:

It shows a theoretical model for accuracy when performing reasoning tasks with an image. The model was developed empirically but for some comparisons and some analytical tasks experimentation has backed it up. I find it a handy thing to have when working out how visualizations and infographics are put together. And when I have some data that I'm designing an representation for, it helps me choose what visual variables to use.

Visualization Techniques for Temporal Information

2007-06-25T13:33:00.000Z

Over the last couple of years I've been collecting various articles and links on temporal information visualisation. I thought it was about time I collated them and tried to put some context and analysis around the various techniques. Here is the article (pdf, 1MB).

Google Timelines

2007-05-25T09:20:00.000Z

From Google Blogoscoped, a fascinating timeline feature found in google experimental. Try volcano, blair, web application.

Social Graphing

2007-04-05T13:44:00.000Z

I mused last year whether we'd see Web 2.0 style entity-link-property visualizations, alla swivel, and today macroscopia arrives. The UI builder looks superficially similar to Yahoo pipes, and it uses a radial layout animation very similar to one I mentioned earlier. Try this for size.

The interaction with the graph feels good - the animation preseves context, is smooth (flash based implementation) and I like the graying of content away from the centre. It is only really good for local link exploration though - no zoom and no other layouts mean the big picture remains elusive.

Some simple search functionality might help for navigation too.

I can't help thinking one thing wrong with this is the complexity in getting the data in - it just isn't easy for your average user to grasp. Putting a good step-by-step goal focused UI on this part would make a big difference.

A sense of universal scale

2007-04-02T09:26:00.000Z

Now that's what I call zooming!

(Put sound on and use the mouse wheel...)

Online Diagramming Web Applications

2007-03-30T09:52:00.000Z

There are a slew of rich internet applications (RIA) out there for drawing and diagramming. Here is a brief review of some notable ones and a list of some others for completeness...

Scrapblog is a feature rich fun web application built using Flex 2. In terms of the smoothness of implementation it is slightly better than Gliffy (Open Lazlo). I guess this more to do with the fun-oriented design of the application rather than the implementation framework. And the embeddability is great - see the blog for some examples.

CumulateDraw is a poor third: similar functionality, but a terrible name, a basic implementation (raw javascript/html?), and poor usability (try the palette) let it down. Last and least, is Thinkature, which looks cool initially, but its limited functionality and slowness mean after a couple of minutes you want to browse elsewhere.

MindMeister might be worth tracking once it launches...

See also Kayuda , Mindomo , yWorks, bubbl.us
mind42, skrbl, ajaxSketch, FlowChart and an oldie: Imagination Cubed

The latest Jonathan Harris

2007-03-16T09:38:00.000Z

Universe. Plus a video explanation.

Geotime and Crime Mapping

2007-03-02T17:21:00.000Z

A dynamic visualisation of crimes over time and space - drag the marker along the top & see what happens. Plus some theory. It isn't perfect by any means, but the ideas are nice & it may be interesting to see where they go with it...

The opposite of usable

2007-02-19T13:16:00.000Z

This video of speech recognition in Vista is so excruciating, it actually ends up being kind of funny...

Flow

2007-02-12T11:55:00.000Z

This charming flash game made me think whether a 'depth' metaphor could work when exposing 'drill down on information'/'collapse or summarize information' in a visual way.

Words, Dictionaries and Thesauri

2007-02-01T11:51:00.000Z

There are several link-entity browsers out there for words. Here are some I've spotted:

Mark Shepherd has a thesaurus browser
a taxonomic approach at Roget2000
the Visuwords Online Graphical Dictionary
an award winning Google widget MapMyWord
the Thinkmap Visual Thesaurus

It is interesting to compare their approaches...

In terms of delivery, the Flash approach of the thesaurus browser and Visuwords wins hands-down.
In terms of keeping one's point of reference (history, animation), Roget2000 fails miserably. The hyperbolic layout kind of works, but it isn't particularly legible.
Visuwords is ugly to the point of distraction, and the layouts hide the words sometimes. Good feedback when dragging though.
MapMyWord appears to work through image maps, and is responsive until you want to re-centre it.
Thinkmap is Java, uses animated radial layout to good effect, and has a plethora of options. Not that I'd actually want to pay for it though!

An honourable mention also has to go to the ObjectGraph Dictionary - great speed and usability through AJAX.

Places mentioned in this book

2007-01-26T12:49:00.000Z

Google Book Search now adds a map of places mentioned in the book. Try War and Peace, or some other examples.

Many Eyes

2007-01-24T09:43:00.000Z

IBM's visualization lab have published the 'Many Eyes' collaborative site, which improves on the ideas of Swivel. After data gets uploaded, you can choose several different visualization paradigms to view it.

Friday Catch Up

2007-01-19T14:07:00.000Z

These flight paths are just stunning.

A hyperbolic graph of data sources from Lexis Nexis - good for graphs with tree structure.

I found this article from Cooper design a good read - particularly the 'revision death spiral'...

And finally - Is this formula for real?

Justice Mapping

2007-01-12T11:54:00.000Z

An elegant set of visualizations of 'justice data'.

Information Visualization Introduction

2007-01-11T09:21:00.000Z

This google tech talk is a great introduction to information visualization theory with particular reference to node-link graphs by a rising star in the field, Tamara Munzner.